Feature extraction of hyperspectral data using the best wavelet packet basis

Pai Hui Hsu, Yi Hsing Tseng

研究成果: Paper

8 引文 斯高帕斯(Scopus)

摘要

An adaptive wavelet decomposition algorithm called the Best Wavelet Packet Basis is used to extract the most useful spectral features from the original hyperspectral data for classification applications. Tested on a set of AVIRIS data, the novel feature extraction method is evaluated and compared with some contemporary feature extraction methods.

原文English
頁面1667-1669
頁數3
出版狀態Published - 2002 一月 1
事件2002 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2002) - Toronto, Ont., Canada
持續時間: 2002 六月 242002 六月 28

Other

Other2002 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2002)
國家Canada
城市Toronto, Ont.
期間02-06-2402-06-28

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Earth and Planetary Sciences(all)

指紋 深入研究「Feature extraction of hyperspectral data using the best wavelet packet basis」主題。共同形成了獨特的指紋。

  • 引用此

    Hsu, P. H., & Tseng, Y. H. (2002). Feature extraction of hyperspectral data using the best wavelet packet basis. 1667-1669. 論文發表於 2002 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2002), Toronto, Ont., Canada.